Quantum DNF Learnability Revisited
نویسندگان
چکیده
We describe a quantum PAC learning algorithm for DNF formulae under the uniform distribution with a query complexity of Õ(s/ǫ+ s/ǫ), where s is the size of DNF formula and ǫ is the PAC error accuracy. If s and 1/ǫ are comparable, this gives a modest improvement over a previously known classical query complexity of Õ(ns/ǫ). We also show a lower bound of Ω(s logn/n) on the query complexity of any quantum PAC algorithm for learning a DNF of size s with n inputs under the uniform distribution.
منابع مشابه
ua nt - p h / 02 02 06 6 v 1 1 2 Fe b 20 02 Quantum DNF Learnability Revisited
We describe a quantum PAC learning algorithm for DNF formulae under the uniform distribution with a query complexity of Õ(s/ǫ+ s/ǫ), where s is the size of DNF formula and ǫ is the PAC error accuracy. If s and 1/ǫ are comparable, this gives a modest improvement over a previously known classical query complexity of Õ(ns/ǫ). We also show a lower bound of Ω(s logn/n) on the query complexity of any...
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